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  Folha Amazônica


TG-03 (Schafer / Artaxo / Duarte / Setzer)

LBA Dataset ID:



2. ECK, T.F.
      4. ARTAXO, P.E.

Point(s) of Contact:

ORNL DAAC User Services Office Oak Ridge National Laboratory Oak Ridge, Tennessee 37 (

Dataset Abstract:

This data set includes Aerosol Optical Thickness Measurements from Cimel Sunphotometer for multiple sites in Brazil during the period from 1993-2005.</b>
The AERONET (AErosol RObotic NETwork) program is an inclusive federation of ground-based remote sensing aerosol networks established by AERONET and PHOTON and greatly expanded by AEROCAN (the Canadian sun-photometer network) and other agency, institute and university partners. The goal is to assess aerosol optical properties and validate satellite retrievals of aerosol optical properties. The network imposes standardization of instruments, calibration, and processing. Data from this collaboration provides globally distributed observations of spectral aerosol optical depths, inversion products, and precipitable water in geographically diverse aerosol regimes.
Three levels of data are available from the AERONET website: Level 1.0 (unscreened), Level 1.5 (cloud-screened), and Level 2.0 (Cloud-screened and quality-assured).
Data provided here are Level 2.0.
Descriptions of program objectives, affiliations, the instrumentation, operational issues, data products, data-base browser demonstrations, research activities, links to similar data sets, NASA EOS links and personnel involved in AERONET may be found at: CAUTION: Data presented in the real-time data version at the AERONET web site are unscreened and may not have final calibration reprocessing. NOTICE TO NON-AERONET INVESTIGATORS:</b> To maintain the integrity of the data base and fairness to the individuals who have contributed, use of these data for publication requires an offer of authorship to the AERONET Principal Investigator(s) PI(s). For each site there is a PI, the person responsible for deployment, maintenance and data collection. The PI is entitled to be informed of any use of that site data.

Beginning Date:


Ending Date:


Metadata Last Updated on:


Data Status:


Access Constraints:


Data Center URL:

Distribution Contact(s):

ORNL DAAC User Services Office Oak Ridge National Laboratory Oak Ridge, Tennessee 37 (

Access Instructions:


Data Access:

IMPORTANT: The LBA-ECO Project website is no longer being supported. Links to external websites may be inactive. Final data products from the LBA project can be found at the ORNL DAAC. Please follow the fair use guidelines found in the dataset documentation when using or citing LBA data.

LBA-ECO TG-03 Aeronet Aerosol Optical Thickness Measurements, Brazil: 1993-2005 :

Documentation/Other Supporting Documents:

LBA-ECO TG-03 Aeronet Aerosol Optical Thickness Measurements, Brazil: 1993-2005 :

Citation Information - Other Details:

Schafer J.S., T. F. Eck, B.N. Holben, P. Artaxo, M.A. Yamasoe, and S. Procopio. 2012. LBA-ECO TG-03 AERONET Aerosol Optical Thickness Measurements, Brazil: 1993-2005. Data set. Available on-line [] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.

Keywords - Theme:

Parameter Topic Term Source Sensor


Keywords - Place (with associated coordinates):

(click to view profile)
(click to view profile)
North South East West
  PARA WESTERN (SANTAREM) -1.19700 -20.44970 -48.28270 -70.31300

Related Publication(s):

Echalar, F., P. Artaxo, J.V. Martins, M. Yamasoe, F. Gerab, W. Maenhaut, and B. Holben. 1998. Long-term monitoring of atmospheric aerosols in the Amazon Basin: Source identification and apportionment. Journal of Geophysical Research-Atmospheres 103(D24):31849-31864.

M. A. Yamasoe. 2006. Effect of smoke and clouds on the transmissivity of photosynthetically active radiation inside the canopy. Atmos. Chem. Phys., 6, 1645-1656.

Oliveira, P.H.F., P. Artaxo, C. Pires, S. De Lucca, A. Procopio, B. Holben, J. Schafer, L.F. Cardoso, S.C. Wofsy, and H.R. Rocha. 2007. The effects of biomass burning aerosols and clouds on the CO2 flux in Amazonia. Tellus Series B-Chemical and Physical Meteorology 59(3):338-349.

Procopio, A.S., et al. 2004. Multiyear analysis of amazonian biomass burning smoke radiative forcing of climate. GRL VOL. 31, L03108, doi:10.1029/2003GL018646.

Schafer et al. 2008, Characterization of the optical properties of atmospheric aerosols in Amazoonia from long-term AERONET monitoring (1993-1995 and 1999-2006). Journal of Geophysical Research, VOL. 113, D04204, doi:10.1029/2007JD009319, 2008.

Schafer, J.S., B.N. Holben, T.F. Eck, M.A. Yamasoe, and P. Artaxo. 2002. Atmospheric effects on insolation in the Brazilian Amazon: Observed modification of solar radiation by clouds and smoke and derived single scattering albedo of fire aerosols. Journal of Geophysical Research-Atmospheres 107(D20):Article-8074.

Schafer, J.S., T.F. Eck, B.N. Holben, P. Artaxo, M.A. Yamasoe, and A.S. Procopio. 2002. Observed reductions of total solar irradiance by biomass-burning aerosols in the Brazilian Amazon and Zambian Savanna. Geophysical Research Letters 29(17):Article-1823.

Data Characteristics (Entity and Attribute Overview):

Data Characteristics:

Aerosol optical thickness (AOT) measurements were obtained at twenty-two sites across the Amazon Basin and are most accurately representative of aerosol conditions within a 10km radius of the observation points.

Each site's data record of AOT is recorded in its own data file. There is no data record between the pre-LBA field work (1993-1995) and the resumption of field activities beginning in 1999. Not all sites have data for all measurement years (1993-1995; 1999-2004). The data provided here are processed to Level 2.0 (cloud-screened and quality assured).

Data are presented in 22 comma separated files. Each file name includes the site name and the inclusive years of sampling as well as the processing level (lev20 represents level 2.0).

Data files are organized as follows:

File name:,000101_050101_Cuiaba_Miranda_lev20.csv

File date:,25_Jan_2012

Associated LME file:,TG03_AERONET_AOT


Version 1 Direct Sun Algorithm, AOT Level 2.0 automatically cloud cleared and manually inspected.,


1,Date,YYYYMMDD,Sampling date : GMT solar day

2,Time,hh:mm:ss,Sampling time GMT

3,Julian_Day,,Sampling date in decimal day of year

4,AOT_1020,,Aerosol optical thickness measured at 1020 nm wavelength

5,AOT_870,,Aerosol optical thickness measured at 870 nm wavelength

6,AOT_670,,Aerosol optical thickness measured at 670 nm wavelength

7,AOT_500,,Aerosol optical thickness measured at 500 nm wavelength

8,AOT_440,,Aerosol optical thickness measured at 440 nm wavelength

9,AOT_380,,Aerosol optical thickness measured at 380 nm wavelength

10,AOT_340,,Aerosol optical thickness measured at 340 nm wavelength

11,AOT_532,,Aerosol optical thickness measured at 532 nm wavelength

12,AOT_535,,Aerosol optical thickness measured at 535 nm wavelength

13,AOT_1640,,Aerosol optical thickness measured at 1640 nm wavelength

14,Water_vapor,g per cm2,Water vapor measured at a 940 nm wavelength

15,TripletVar_1020,%,AOT triplet variability expressed in percent for measurements at 1020 nanometer wavelength

16,TripletVar_870,%,AOT triplet variability expressed in percent for measurements at 870 nanometer wavelength

17,TripletVar_670,%,AOT triplet variability expressed in percent for measurements at 670 nanometer wavelength

18,TripletVar_500,%,AOT triplet variability expressed in percent for measurements at 500 nanometer wavelength

19,TripletVar_440,%,AOT triplet variability expressed in percent for measurements at 440 nanometer wavelength

20,TripletVar_380,%,AOT triplet variability expressed in percent for measurements at 380 nanometer wavelength

21,TripletVar_340,%,AOT triplet variability expressed in percent for measurements at 340 nanometer wavelength

22,TripletVar_532,%,AOT triplet variability expressed in percent for measurements at 532 nanometer wavelength

23,TripletVar_535,%,AOT triplet variability expressed in percent for measurements at 535 nanometer wavelength

24,TripletVar_1640,%,AOT triplet variability expressed in percent for measurements at 1640 nanometer wavelength

25,WaterError,%,Error associated with water vapor measurement expressed in percent

26,440-870Angstrom,,Angstrom exponent calculated between wavelengths of 440 and 870 nanometers

27,380-500Angstrom,,Angstrom exponent calculated between wavelengths of 380 and 500 nanometers

28,440-675Angstrom,,Angstrom exponent calculated between wavelengths of 440 and 675 nanometers

29,500-870Angstrom,,Angstrom exponent calculated between wavelengths of 500 and 870 nanometers

30,340-440Angstrom,,Angstrom exponent calculated between wavelengths of 340 and 440 nanometers

31,440-675Angstrom(Polar),,Angstrom exponent calculated between wavelengths of 440 and 675 nanometers (polar)

32,Last_Processing_Date,,Date of last data processing

33,Solar_Zenith_Angle,degrees,Solar zenith angle

,missing data is represented by -9999

Sample data
















Data Application and Derivation:

The radiometer makes two basic measurements, either direct sun or sky, both within several programmed sequences. The direct sun measurements are made in eight spectral bands requiring approximately 10 seconds. Eight interference filters at wavelengths of 340, 380, 440, 500, 670, 870, 940 and 1020 nm are located in a filter wheel which is rotated by a direct drive stepping motor. The 940 nm channel is used for column water abundance determination. A preprogrammed sequence of measurements is taken by these instruments starting at an airmass of 7 in the morning and ending at an airmass of 7 in the evening. Optical thickness is calculated from spectral extinction of direct beam radiation at each wavelength based on the Beer-Bouguer Law. Attenuation due to Rayleigh scatter, and absorption by ozone (from interpolated ozone climatology atlas), and gaseous pollutants is estimated and removed to isolate the aerosol optical thickness (AOT).

Quality Assessment (Data Quality Attribute Accuracy Report):

Quality Assessment:

The data undergo preliminary processing (real time data), reprocessing (final calibration ~6 mo. after data collection), quality assurance, archiving and distribution from NASA\'s Goddard Space Flight Center master archive.

Calibration relies upon determination of the calibration coefficients needed to convert the instrument output digital number (DN) to a desired output, in this case aerosol optical thickness (AOT), precipitable water, and radiance (W/m2/sr/um).

The Langley Plot is a logarithm of the DN taken during these times plotted against the optical airmass between a range of 5 and 2 (between 3.5 and 2 for 340 nm), where the intercept is the calibration coefficient (zero airmass DN) and the slope is the optical thickness. Langley plots from NOAA\'s Mauna Loa Observatory have been made to determine the spectral extraterrestrial voltage for these instruments since 1994. The observatory\'s high altitude and isolation from most local and regional sources of aerosols provides a very stable irradiance regime in the mornings, and is ideally suited to our purposes.

AERONET reference instruments are typically recalibrated at NOAA\'s Mauna Loa Observatory every 2-3 months using the Langley plot technique. The zero air mass voltages [Vo, instrument voltage for direct normal solar flux extrapolated to the top of the atmosphere (Shaw, 1983)] are inferred to an accuracy of approximately 0.2 to 0.5% for the MLO calibrated reference instruments (Holben et al., 1998). Therefore the uncertainty in AOT due to the uncertainty in zero airmass voltages for the reference instruments is better than 0.002 to 0.005.

The Sun-sky radiometers at sites other than GSFC are intercalibrated against a MLO calibrated AERONET reference instrument both before deployment in the field and post- deployment. A linear rate of change in time of the zero airmass voltages is then assumed in the processing of the data from field sites. Our analysis suggests that this results in an uncertainty of approximately 0.01 - 0.02 in AOT (wavelength dependent) due to calibration uncertainty for the field instruments.

A sequence of three AOT measurements are taken 30 seconds apart creating a triplet observation per wavelength. During the large airmass periods direct sun measurements are made at 0.25 airmass intervals, while at smaller airmasses the interval between measurements is typically 15 minutes. The time variation of clouds is usually greater than that of aerosols causing an observable variation in the triplets that can be used to screen clouds in many cases. Additionally the 15-minute interval allows a longer temporal frequency check for cloud contamination.

Process Description:

Data Acquisition Materials and Methods:

Data are transmitted hourly or half hourly from the memory of the sun photometer microprocessor via the Data Collection Systems (DCS) to either of three geosynchronous satellites GOES, METEOSAT or GMS and then retransmitted to the appropriate ground receiving station. The data can be retrieved for processing by Internet linkage resulting in near real-time acquisition from almost any site on the globe excluding poleward of 80 degrees latitude. The DCS is a governmental system operated for the purpose of transmitting low volume environmental data from remote sites for various institutions and government agencies.

The frequencies, channels and transmission windows are assigned by NOAA NESDIS for GOES, EUMETSAT for METEOSAT and GMS which are broadcast in the 401 to 402 MHz range. The satellite transmitter module used is a Vitel VX1004 which is commercially modified for use with the CE 318 A (The Vitel VX1004/2 is used by the PHOTON group but it is no longer in production). The antenna is conical approximately 40 cm in diameter and 40 cm long. The transmitter system is battery operated and charged by a 10 watt solar panel.




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